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Realistic effective interparticle interactions of quantum many-body systems are widely seen as being short-range. However, the rigorous mathematical analysis of this type of model turns out to be extremely difficult, in general, with many…

Mathematical Physics · Physics 2023-10-09 J. -B. Bru , W. de Siqueira Pedra , K. Rodrigues Alves

Consider a finite system of diffusing particles coupled through a reactive boundary. Each particle is reflected, but may react with the boundary according to a killing mechanism which depends on the current reactivity of the boundary and…

Probability · Mathematics 2026-05-20 Eliana Fausti , Andreas Sojmark

In this work, we consider general exchangeable quantum mean-field Hamiltonian such as the prominent quantum Curie-Weiss model under the influence of a random external field. Despite being arguably the simplest class of disordered quantum…

Mathematical Physics · Physics 2025-12-29 Chokri Manai

The well-posedness of a multi-population dynamical system with an entropy regularization and its convergence to a suitable mean-field approximation are proved, under a general set of assumptions. Under further assumptions on the evolution…

Analysis of PDEs · Mathematics 2022-10-04 Stefano Almi , Claudio D'Eramo , Marco Morandotti , Francesco Solombrino

We consider large systems of particles interacting through rough but bounded interaction kernels. We are able to control the relative entropy between the $N$-particle distribution and the expected limit which solves the corresponding Vlasov…

Analysis of PDEs · Mathematics 2015-11-13 Pierre-Emmanuel Jabin , Zhenfu Wang

This work focuses on the mean field stochastic partial differential equations with nonlinear kernels. We first prove the existence and uniqueness of strong and weak solutions for mean field stochastic partial differential equations in the…

Probability · Mathematics 2025-08-19 Wei Hong , Shihu Li , Wei Liu

We study stochastic particle systems on a complete graph and derive effective mean-field rate equations in the limit of diverging system size, which are also known from cluster aggregation models. We establish the propagation of chaos under…

Probability · Mathematics 2021-07-21 Watthanan Jatuviriyapornchai , Stefan Grosskinsky

We report on a simple strategy to treat mean-field limits of quantum mechanical systems in which a large number of particles weakly couple to a second-quantized radiation field. Extending the method of counting, introduced in [Lett. Math.…

Mathematical Physics · Physics 2021-04-27 Nikolai Leopold , Peter Pickl

We study the mean-field limit of a model of biological neuron networks based on the so-called stochastic integrate-and-fire (IF) dynamics. Our approach allows to derive a continuous limit for the macroscopic behavior of the system, the…

Probability · Mathematics 2023-09-11 Pierre-Emmanuel Jabin , Datong Zhou

Kinetic Ising models are powerful tools for studying the non-equilibrium dynamics of complex systems. As their behavior is not tractable for large networks, many mean-field methods have been proposed for their analysis, each based on unique…

Disordered Systems and Neural Networks · Physics 2021-05-13 Miguel Aguilera , S. Amin Moosavi , Hideaki Shimazaki

We consider interacting particle systems with unbounded interaction range on general countably infinite graphs $S$ and prove explicit non-asymptotic error bounds for approximations of the infinite-volume dynamics by systems of finitely many…

Probability · Mathematics 2026-03-24 Benedikt Jahnel , Jonas Köppl

We study the mean-field limit of a generic class of dynamic co-evolving latent space networks motivated by the social and opinion dynamics literature. Such models include $n$ agents, whose opinions are given by latent stochastic processes,…

Probability · Mathematics 2026-04-24 Ankan Ganguly , Konstantinos Spiliopoulos , Daniel Sussman

This paper develops a non-asymptotic approach to mean field approximations for systems of $n$ diffusive particles interacting pairwise. The interaction strengths are not identical, making the particle system non-exchangeable. The marginal…

Probability · Mathematics 2026-04-17 Daniel Lacker , Lane Chun Yeung , Fuzhong Zhou

Understanding the relationship between the heterogeneous structure of complex networks and cooperative phenomena occurring on them remains a key problem in network science. Mean-field theories of spin models on networks constitute a…

Disordered Systems and Neural Networks · Physics 2022-02-10 Fernando L. Metz , Thomas Peron

In the nonlinear diffusion framework, stochastic processes of McKean-Vlasov type play an important role. In some cases they correspond to processes attracted by their own probability distribution: the so-called self-stabilizing processes.…

Probability · Mathematics 2014-09-04 Samuel Herrmann , Julian Tugaut

In this paper, we study multi-species stochastic interacting particle systems and their mean-field McKean-Vlasov partial differential equations (PDEs) in non-convex landscapes. We discuss the well-posedness of the multi-species SDE system,…

Probability · Mathematics 2025-07-11 Manh Hong Duong , Grigorios A. Pavliotis , Julian Tugaut

Classical spin systems with nonadditive long-range interactions are studied in the microcanonical ensemble. It is expected that the entropy of such a system is identical to that of the corresponding mean-field model, which is called…

Statistical Mechanics · Physics 2012-06-29 Takashi Mori

All current formulations of nonequilibrium thermodynamics of open chemical reaction networks rely on the assumption of non-interacting species. We develop a general theory which accounts for interactions between chemical species within a…

Statistical Mechanics · Physics 2021-03-09 Francesco Avanzini , Emanuele Penocchio , Gianmaria Falasco , Massimiliano Esposito

We study interacting particle systems of Kuramoto-type. Our focus is on the dynamical relation between the partial differential equation (PDE) arising in the continuum limit (CL) and the one obtained in the mean-field limit (MFL). Both…

Dynamical Systems · Mathematics 2025-11-07 Christian Kuehn , Giacomo Landi

This paper introduces and analyzes a new class of mean-field control (\textsc{MFC}) problems in which agents interact through a \emph{fixed but controllable} network structure. In contrast with the classical \textsc{MFC} framework -- where…

Optimization and Control · Mathematics 2025-11-07 Mao Fabrice Djete